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ICmetrics for Low Resource Embedded Systems

Kovalchuk, Yevgeniya and Hu, Huosheng and Gu, Dongbing and McDonald-Maier, Klaus D. and Howells, Gareth (2012) ICmetrics for Low Resource Embedded Systems. In: 2012 Third International Conference on Emerging Security Technologies. IEEE, pp. 121-126. ISBN 978-1-4673-2448-9. E-ISBN 978-0-7695-4791-6. (doi:10.1109/EST.2012.23) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1109/EST.2012.23

Abstract

The ICmetrics technology is based on extracting features from digital devices' operation that may be integrated together to generate unique identifiers for each of the devices or create unique profiles that describe the devices' actual behaviour. Any changes in these identifiers (profiles) during consequent devices' operation would signal about a possible safety or security breach within the electronic system. This paper explores the program counter (PC) of a processor core as a potential source for ICmetrics features and discusses several methods of feature values acquisition with the aim to achieve a maximum level of information gain with a minimal impact on a system's performance. The main finding of this study is that while isolated PC values may not always allow to generate a stable identifier (profile) for a device that would distinguish the device from the rest in the considered set, the PC sequences and frequencies in the execution flow may serve as suitable ICmetrics features, which has yet to be tested in complex scenarios.

Item Type: Book section
DOI/Identification number: 10.1109/EST.2012.23
Uncontrolled keywords: sampling methods; image color analysis; security; embedded systems; feature extraction; educational institutions
Subjects: T Technology
Divisions: Faculties > Sciences > School of Engineering and Digital Arts > Image and Information Engineering
Depositing User: Tina Thompson
Date Deposited: 31 Oct 2013 14:25 UTC
Last Modified: 24 Sep 2019 12:52 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/35892 (The current URI for this page, for reference purposes)
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